Tracked vehicles distribute their weight continuously over a large surface area (the tracks). This distinctive feature makes them the preferred choice for vehicles required to traverse soft and uneven terrain. From a robotics perspective, however, this flexibility comes at a cost: the complexity of modelling the system and the resulting difficulty in designing theoretically sound navigation solutions. In this paper, we aim to bridge this gap by proposing a framework for the navigation of tracked vehicles, built upon three key pillars. The first pillar comprises two models: a simulation model and a control-oriented model. The simulation model captures the intricate terramechanics dynamics arising from soil-track interaction and is employed to develop faithful digital twins of the system across a wide range of operating conditions. The control-oriented model is pseudo-kinematic and mathematically tractable, enabling the design of efficient and theoretically robust control schemes. The second pillar is a Lyapunov-based feedback trajectory controller that provides certifiable tracking guarantees. The third pillar is a portfolio of motion planning solutions, each offering different complexity-accuracy trade-offs. The various components of the proposed approach are validated through an extensive set of simulation and experimental data.

翻译：履带式车辆通过连续接触的大面积（履带）分散其重量。这一独特特性使其成为需要在松软不平地形中行驶的车辆的首选。然而，从机器人学的角度来看，这种灵活性带来了代价：系统建模的复杂性以及由此导致的设计理论上可靠的导航解决方案的困难。本文旨在通过提出一个基于三个关键支柱的履带式车辆导航框架来弥合这一差距。第一个支柱包含两个模型：一个仿真模型和一个面向控制的模型。仿真模型捕捉了由土壤-履带相互作用产生的复杂地面力学动力学，并用于在各种操作条件下开发系统的高保真数字孪生。面向控制的模型是伪运动学的且在数学上易于处理，从而能够设计高效且理论鲁棒的控制方案。第二个支柱是一个基于李雅普诺夫的反馈轨迹控制器，它提供了可证明的跟踪保证。第三个支柱是一系列运动规划解决方案，每种方案都提供了不同的复杂度-精度权衡。所提出方法的各个组成部分通过大量的仿真和实验数据得到了验证。